fix: copy size array before reorder in multi-color scatter plots

[Ekin-Kahraman]

Summary

Fixes #4024.

• Root cause: In embedding(), the per-point size array was reordered in-place (size = np.array(size)[order]) inside the per-color loop. Each iteration's z-order permutation was applied to the already-reordered array from the previous iteration, causing cumulative corruption of marker sizes across subplots.
• Fix: Use a loop-local variable _size so each iteration reorders from the original size array. This matches the behavior of color_source_vector, color_vector, and coords, which are all freshly derived each iteration.

Changes

• src/scanpy/plotting/_tools/scatterplots.py: Replace in-place mutation of size with a loop-local _size variable; update all downstream references within the loop body.
• tests/test_plotting.py: Add test_scatter_size_not_mutated_across_panels regression test that verifies the input size array is not modified after plotting with multiple color keys.

Test plan

• test_scatter_size_not_mutated_across_panels passes — confirms the size array is preserved
• Existing scatter/embedding tests continue to pass (no behavioral change for single-panel plots or scalar sizes)

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 78.51%. Comparing base (9bc2c1e) to head (0d33cf7).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #4040      +/-   ##
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- Coverage   78.51%   78.51%   -0.01%     
==========================================
  Files         117      117              
  Lines       12753    12752       -1     
==========================================
- Hits        10013    10012       -1     
  Misses       2740     2740              

Flag	Coverage Δ
hatch-test.low-vers	77.80% <100.00%> (-0.01%)	⬇️
hatch-test.pre	77.47% <100.00%> (+12.63%)	⬆️

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Files with missing lines	Coverage Δ
src/scanpy/plotting/_tools/scatterplots.py	83.48% <100.00%> (-0.04%)	⬇️